The Application of Data Envelopment Analysis Methodology to Improve the Benchmarking Process in the EFQM Business Model
محورهای موضوعی : Operation Research
1 - Department of Industrial management, Islamic Azad University, Rasht branch
کلید واژه: Data envelopment analysis, EFQM Excellence Model, Wilcoxon Rank Sum Test, Benchmarking, Road map,
چکیده مقاله :
This paper reports a survey and case study research outcomes on the application of Data Envelopment Analysis (DEA) to the ranking method of European Foundation for Quality Management (EFQM) Business Excellence Model in Iran’s Automotive Industry and improving benchmarking process after assessment. Following the global trend, the Iranian industry leaders have introduced the EFQM practice to their supply chain in order to improve the supply base competitiveness during the last four years. A question which is raises is whether the EFQM model can be combined with a mathematical model such as DEA in order to generate a new ranking method and develop or facilitate the benchmarking process. The developed model of this paper is simple. However, it provides some new and interesting insights. The paper assesses the usefulness and capability of the DEA technique to recognize a new scoring system in order to compare the classical ranking method and the EFQM business model. We used this method to identify meaningful exemplar companies for each criterion of the EFQM model then we designed a road map based on realistic targets in the criterion which have currently beenachieved by exemplar companies. The research indicates that the DEA approach is a reliable tool to analyze the latent knowledge of scores generated by conducting self- assessments. The Wilcoxon Rank Sum Test is used to compare two scores and the Test of Hypothesis reveals the meaningful relation between the EFQM and DEA new ranking methods. Finally, we drew a road map based on the benchmarking concept using the research results.
This paper reports a survey and case study research outcomes on the application of Data Envelopment Analysis (DEA) to the ranking method of European Foundation for Quality Management (EFQM) Business Excellence Model in Iran’s Automotive Industry and improving benchmarking process after assessment. Following the global trend, the Iranian industry leaders have introduced the EFQM practice to their supply chain in order to improve the supply base competitiveness during the last four years. A question which is raises is whether the EFQM model can be combined with a mathematical model such as DEA in order to generate a new ranking method and develop or facilitate the benchmarking process. The developed model of this paper is simple. However, it provides some new and interesting insights. The paper assesses the usefulness and capability of the DEA technique to recognize a new scoring system in order to compare the classical ranking method and the EFQM business model. We used this method to identify meaningful exemplar companies for each criterion of the EFQM model then we designed a road map based on realistic targets in the criterion which have currently beenachieved by exemplar companies. The research indicates that the DEA approach is a reliable tool to analyze the latent knowledge of scores generated by conducting self- assessments. The Wilcoxon Rank Sum Test is used to compare two scores and the Test of Hypothesis reveals the meaningful relation between the EFQM and DEA new ranking methods. Finally, we drew a road map based on the benchmarking concept using the research results.
[1] Donnelly M., A radical scoring system for the European Foundation for Quality Management Business Excellence Model, Managerial Auditing Journal,15, 1-12, 2000.
[2] Westlund A. H., Measuring environmental impact on society in the EFQM system, Total Quality Management, 12(1), 125-35, 2001.
[3] Hillman G.P., Making self-assessment successful, The TQM Magazine, 6, 29-31, 1994.
[4] Porter L., and Tanner S., Assessing Business Excellence , Buttrworth- Heinemann, Oxford, 1996.
[5] Van der Wiele T., Dale B. And Williams R., Business improvement through quality management system, Management Decision, 38(1), 19-23, 2000.
[6] Ghobadian A., and Woo H. S., Characteristics, benefits and shortcomings of four major quality award, International Journal of Quality&Reliability Management, 13(2), 10-44, 1996.
[7] Zhu J., Quantitative Model for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets and DEA Excel Solver, Kluwer Academic Publishers, Boston, 2002.
[8] Charnes A., Cooper, W.W. and Rhodes, E., Measuring the efficiency of decision making units, European Journal of Operation Research, 2, 429-44, 1978.
[9] Farrel M.J., The measurement of productive efficiency, Journal of Royal Statistical Society A, 120, 253-281, 1957.
[10] Arnold V., Bardhan I., Cooper W. W., and Gallegos A., Primal and Dual Optimality in Computer Codes Using Two-Stage Solution Procedures in DEA, Operations Research Methods, Models and Applications (Westpost, conn: Quorum Books), 1998.
[11] Schmidt A., and Zink K. J., Practice and implementatin of self-assessment, International Journal of Quality Science, 3, 5-17, 1998.
[12] Ritchie L., and Dale B.G., An analysis of the self-assessment practice using the business excellence model, Proceeding of the Institution of Mechanical Engineers, 204(B4), 593-602, 2000.
